| name | aliyun-qwen-asr-realtime |
| description | Use when low-latency realtime speech recognition is needed with Alibaba Cloud Model Studio Qwen ASR Realtime models, including streaming microphone input, live captions, or duplex voice agents. |
| version | 1.0.0 |
Category: provider
Model Studio Qwen ASR Realtime
Validation
mkdir -p output/aliyun-qwen-asr-realtime
python -m py_compile skills/ai/audio/aliyun-qwen-asr-realtime/scripts/prepare_realtime_asr_request.py && echo "py_compile_ok" > output/aliyun-qwen-asr-realtime/validate.txt
Pass criteria: command exits 0 and output/aliyun-qwen-asr-realtime/validate.txt is generated.
Output And Evidence
- Save session payloads and response samples under
output/aliyun-qwen-asr-realtime/.
Critical model names
Use one of these exact model strings:
qwen3-asr-flash-realtime
qwen3-asr-flash-realtime-2026-02-10
Use cases
- Realtime subtitles and captions
- Voice-agent duplex input
- Streaming speech-to-text in browser or terminal clients
Prerequisites
- Set
DASHSCOPE_API_KEY in your environment, or add dashscope_api_key to ~/.alibabacloud/credentials.
- Realtime sessions generally require WebSocket or streaming session handling in the client.
Normalized interface (asr.realtime)
Request
model (string, optional): default qwen3-asr-flash-realtime
language_hints (array, optional)
format (string, optional): e.g. pcm, wav
sample_rate (int, optional): e.g. 16000
chunk_ms (int, optional): frame size in milliseconds
Response
text (string): recognized transcript fragment
is_final (bool): finalization marker
usage (object, optional)
Quick start
Generate a request template:
python skills/ai/audio/aliyun-qwen-asr-realtime/scripts/prepare_realtime_asr_request.py \
--output output/aliyun-qwen-asr-realtime/request.json
Operational guidance
- Prefer 16kHz mono PCM unless your client stack requires another format.
- Keep chunks small enough for responsive partial results.
- If you only have recorded files, use
skills/ai/audio/aliyun-qwen-asr/ instead.
References